This assignment is for ETC5521 Assignment 1 by Team goanna comprising of XUE WANG, XITONG HE, and CUIPING WEI.

Soure: Bushfires ravaged Australia

1 Introduction and motivation

Bushfires that raged in Australia from September 2019 to early 2020 captured the attention of people worldwide, especially the out-of-control bushfires in Victoria and New South Wales(NSW). However, looking at the Australian bushfires’ history data, we can find that Australia suffers from different degrees and quantities of bushfires every year. It is exciting to explore the link between Australian fire history and climate change. What climatic conditions caused the frequent occurrence of the bushfires in Australia?
In this analysis, R is the main tool for data cleaning and analysis.
The rest of the analysis proceeds as follows. Section 2 presents the data description. Section 3 details the findings in data analysis. The limitations of the analysis are presented in Section 4. Finally, Section 5 provides the conclusions of this analysis.

1.1 Research questions

This analysis aims to explore three secondary questions:
- When and where were the most widespread fires burning?
- Was temperature to be blamed for bushfires in Australia?
- Was rainfall to be blamed for bushfires in Australia?

2 Data description

This section mainly introduces the data, data sources and data description.
There are three data sets used on this analysis, and the cleaned data is obtained from GitHub tidytuesday.

2.1 Australua fire data

The fire data source is from NASA(NASA 2020) “Active Fires Dataset” via the MODIS fire product collection. MODIS active fire product is detected the fire data in every 5 minutes and collected through each tile with horizontal and vertical coordinate.The data contains the fire information of Australia with 5101817 observations from 2000-11-01 to 2020-01-05.
The variables information included in the data are as the following table, latitude, longitude and acq_date variables were mainly used for this analysis.

Table 2.1: Australia fire data
Variable Description
latitude Center of 1km fire pixel but not necessarily the actual location of the fire as one or more fires can be detected within the 1km pixel.
longitude Center of 1km fire pixel but not necessarily the actual location of the fire as one or more fires can be detected within the 1km pixel.
brightness Channel 21/22 brightness temperature of the fire pixel measured in Kelvin.
scan The algorithm produces 1km fire pixels but MODIS pixels get bigger toward the edge of scan. Scan and track reflect actual pixel size.
track The algorithm produces 1km fire pixels but MODIS pixels get bigger toward the edge of scan. Scan and track reflect actual pixel size.
acq_date Date of MODIS acquisition.
act_time Time of acquisition/overpass of the satellite (in UTC).
satellite A = Aqua and T = Terra.
confidence This value is based on a collection of intermediate algorithm quantities used in the detection process. It is intended to help users gauge the quality of individual hotspot/fire pixels. Confidence estimates range between 0 and 100% and are assigned one of the three fire classes (low-confidence fire, nominal-confidence fire, or high-confidence fire).
version Version identifies the collection (e.g. MODIS Collection 6) and source of data processing: Near Real-Time (NRT suffix added to collection) or Standard Processing (collection only). ‘6.0NRT’ - Collection 6 NRT processing.’6.0’ - Collection 6 Standard processing. Find out more on collections and on the differences between FIRMS data sourced from LANCE FIRMS and University of Maryland.
dbright_t31 Channel 31 brightness temperature of the fire pixel measured in Kelvin.
frq Depicts the pixel-integrated fire radiative power in MW (megawatts).
day_night D = Daytime, N = Nighttime

2.2 Climate data

For climate data, temperature and rainfall was gathered from the Australian Bureau of Meterology (BoM), of which is used the weather station to measure a variety of aspects of the weather.

The Rainfall data was sourced from six major Australian cities: Perth, Adelaide, Melbourne, Sydney,Brisbane and Canberra, and the cleaned data is obtained from GitHub tidytuesday, which is from 1858-01-01 to 2020-01-06, containing more than 230,000 observations. In order to maintain the complete information in six cities, we added some missing values for Brisbane and Canberra from the source website and cleaned them to obtain the data from 1968-01-01 to 2017-12-31 in Canberra and from 1893-01-01 to 1998-12-31 in Brisbane. The new rainfall data is constructed by the old one and supplemental one and then become the final rainfall data set.

The temperature data is divided into two parts, with the cleaned data obtained directly from GitHub tidytuesday, which is from 1910-01-01 to 2019-05-31. And we found the time range of the cleaned temperature data cannot match the fire data, in order to further analysis of the relationship between the fire and the temperature, we decided to download the new temperature data from the source website, and cleaned it to obtain the new data from 2019-06-01 to 2020-01-05. Finally, the new data were merge with the Github data to produce a final temperature data from 1910-01-01 to 2020-01-05, with more than 530,000 observations.

Also, there are seven weather stations were chosen, based on seven Australian cities such as Perth, Adelaide, Melbourne, Sydney, Brisbane, Port Lincoln and Canberra.

The climate data structure is shown as the below tables.In this analysis, date, temperature and temp_type variables for temperature data set were mainly used, and year, city_name and rainfall variables for rainfall data set as well.

Table 2.2: Temperature data
Variable Class Description
city_name character City Name
date double Date
temperature double Temperature in Celsius
temp_type character Temperature type (min/max daily)
site_name character Actual site/weather station
Table 2.3: Rainfall data
Variable Class Description
station_code character Station Code
city_name character City Name
year double year
month character month
day character day
rainfall double Trainfall in millimeters
period double how many days was it collected across
quality character Certified quality or not
lat double latitude
long double longitude
station_name character Station Name

3 Analysis and findings

3.1 When and where were the most widespread bushfires burning?

The Australian climate is generally hot and dry, bushfires can occur at anytime of the year for the most of regions(Australia 2020). However, are there more bushfires prefer happened in the summer or winter? Did bushfires more likely to occur in Northern Territory(NT)? In this section, we will discuss it by analyzing the bushfire data for the past 20 years.

3.1.1 Which month did bushfires prefer?

The number of Australian fires in 12 month between 2001 and 2020

Figure 3.1: The number of Australian fires in 12 month between 2001 and 2020

From Figure 3.1, there are some unusual phenomena. Firstly, we can see that the bushfires trend line in 2019 is quite different from other years, the main reason for that is the occurrence of extensive bushfires in Australia for 2019. And the bushfires from September 2019 is the most massive bushfire since European settlement(Nolan et al. 2020). Moreover, there was a significant increase in the number of bushfires in September 2011, far more than in any other year in the same period. As Blanchi et al. (2014) states, the combination of low rainfalls and strong winds led to the outbreak of bushfires in 2011.

Average monthly rainfall from 2001

Figure 3.2: Average monthly rainfall from 2001

Also, it’s interesting to find that bushfires are more likely to occur in May, and month from August to November, especially October. However, August to October is the winter to spring period in Australia. It seems that the frequent occurrence of bushfires during this period mainly due to dryness, which makes forest fuels more likely to catch fire(Sullivan et al. 2012). Moreover, comparing with Figure 3.2, it can be easy to find that the driest months are September, October and May, which coincided with the peak of the bushfires.

3.1.2 Which location did bushfires prefer?

In this part, we will focus on the relationship between bushfires and geographic locations. Firstly, we divided fire data into different states or regions according to the latitude and longitude, because the data downloaded from NASA does not contain information for states or regions. Since the borders of NSW and Victoria are not easily distinguished, so we finally putting them together as one region.

The number of bushfire in different states or regions in the past 20 years

Figure 3.3: The number of bushfire in different states or regions in the past 20 years

Figure 3.3 shows the most of bushfires happened in the Northern Territory(NT) and Queensland, probably because both areas are more likely prone to drought and they have more forests. As for VIC_NSW, the overall trend is relatively stable, but the number of fires in 2019 rose significantly. As mentioned in 3.1.1, there were massive bushfires in 2019. Figure 3.4 shows the bushfires distribution from the end of December 2019 to the beginning of January 2020, and we can find that it is mainly concentrated in Victoria and NSW.
Based on the above analysis, we are more curious about what caused the bushfires in Australia. Are there any special climate conditions? We will elaborate on the story of climate conditions and bushfires in Section 3.2 and 3.3.

Figure 3.4: The distribution point for Australian bushfires from 2019-12-29 to 2020-01-05(the darker the color, the more serious the fire)

3.2 The higher the temperature, the more bushfires

Were bushfires more likely to happen with higher temperatures in Australia? In this section, we will explore the relationship between the two in-depth.

Figure 3.5: Annual average temperature trends from 1910 to 2019, calculated by daily maximum temperature

As a first step, we calculated the annual average temperature from 1910 to 2019 and drew a time series plot. From the Figure 3.5, it can be seen that the average temperature in 2019 is significantly higher than in other years. A strong positive Indian Ocean Dipole (IOD) phenomenon was the culprit(Harris and Lucas 2019), and contributed to very high temperature and low rainfall across Australia(Meteorology 2019), which began in May 2019 and lasted until the end of the year.

Indian Ocean Dipole: positive phase. Source from Australian BOM.

Figure 3.6: Indian Ocean Dipole: positive phase. Source from Australian BOM.

However, how big is the difference between the temperature in 2019 and other years?

Therefore, we calculated the annual average temperature from 1961 to 1990, which is the baseline used by the Australian BOM to compare annual average temperature difference. From the Figure 3.7, we can find that from 1910 to mid-1950, the annual average temperature of almost all years was lower than the baseline, but since the late 1950s, it was higher than the baseline. Although there have been sporadic years of unusual trends, it does not affect the overall trend. Also, it is worth noting that 2019 is significantly higher than in other years, with a difference of above 1.5°C. As Meteorology (2019) sates, 2019 was Australia’s warmest year on record, surpassing the previous record of +1.35°C in 2013.

Since the 1970s, the rising average annual temperature has been a warning that Global warming is a growing problem. Moreover, Global warming brings many catastrophic disasters, among which bushfires are one of them. Also, the average temperature in Australia has risen by 1°C since the industrial period, which is one of the reasons why bushfires were so frequently occurred in Australia and raged in 2019(Council 2019).

The plot for the difference between the average temperature of 1961-1990(as baseline) and the annual average temperature for each year from 1910 to 2019, calculated by daily maximum temperature

Figure 3.7: The plot for the difference between the average temperature of 1961-1990(as baseline) and the annual average temperature for each year from 1910 to 2019, calculated by daily maximum temperature

Figure 3.8: Annual total fires trends from 2001 to 2019

Figure 3.8 shows the annual trend of total number of fires in Australia from 2001 to 2019. Compared with Figure 3.5, the annual total fire occurrences trend fluctuates mostly in a consistent pattern. When the temperature is high, there are generally more fires, and vice versa. However, there are an unexpected fact that the fires occurrence in 2012 ranked first with 474,964, but the annual average temperature in 2012 was relatively low with 22.57°C. And we found that the raged bushfires in 2012 that were caused by lightning at the beginning, and lightning was predominantly responsible for the bushfires(Dowdy and Mills 2012).
From the above analysis, we can further clarify that the high-temperature weather in 2019 is closely related to bushfires, and high temperature makes forest fuels more susceptible to cause bushfires(G. J. van Oldenborgh et al. 2020).

3.3 The less rainfall, the more bushfires

Has the less rainfall affected the more bushfires in Australia? Or has the more rainfall influenced the less bushfires? Because of the location of Australia, the rainfall in Australia is highly variable, which is strongly influenced by global climate system phenomena such as El Niño, La Niña, and IOD. Despite this large natural variability, the potential long-term trends are evident in some regions, even effecting the local rainfall.
In this section, we will explore the relationship between rainfall and bushfires, is it positive or negative?

As a first step, we analyzed the overall situation of annual rainfall. There are six cities in rainfall data, of which Sydney has been recorded the rainfall data from 1850, but most of the other cities start from around 1970. Therefore, we selected the rainfall data from 1970 for using the same scale in the year variable. To calculate the annual average rainfall situation, using the six cities which are from six states or regions in Australia to estimate the overall yearly average rainfall. Also, we calculated the annual average rainfall from 1961 to 1990, which is the baseline used by the Australian BOM to compare annual average rainfall difference(Meteorology 2019).

Figure 3.9: Annual total rainfall trends from 2001 to 2019

Figure 3.9 shows how the annual rainfall has changed over time in Australia. An extremely severe drought occurred in 1994, and this drought was influenced by a healthy El Niño weather pattern, the fifth continuous year of drought in parts of Australia(Nicholls 2004). Also, although the variability of natural weather in Australia is vast, 2019 became the driest year in the recent 20 years. One reason is that the strongest positive IOD reached the highest values on record across 60 years, and due to the frequency and influence of sea-surface temperature changes, the El Nino-Southern Oscillation(ENSO) is neutral throughout the year. Because of the positive IOD, it severely curtailed the Walker Circulation, and abnormal easterly winds appear in the Indian Ocean and prevailing winds in northwest Australia blow from the continent to the ocean. These winds swept away large amounts of cloud cover over Australia, so the rainfall has been declined dramatically based on that(Hughes 2003). Also, the annual rainfall in 2010 was the highest in 20 years, which is the wettest year since 2000 because of the climate system such as La Niña events.

Comparing with Figure 3.8, the number of bushfires in Australia has fluctuated but the average of fire more than 250,000 cases in each year in the last 20 years. And the number of total bushfires is the lowest one in 2010, possibly because of the highest annual rainfall in 2010, which can be contributed to dry relief conditions and reduce the fuel load leading.

From Figure 3.10, the annual average rainfall changed cross-time compare with the average baseline. The overall situation is that the rainfall difference of most of the years is below the average, especially for the last 20 years. Even though the annual rainfall difference is above the baseline but it is still above a few in 2010 and 2011. Also, 2019 is still the lowest rainfall difference in the recent 20 years.

Annual rainfall difference

Figure 3.10: Annual rainfall difference

From the above analysis, we can make some insights that the low rainfall in 2019 is closely related to bushfires.

3.4 The correlation between climatic conditions and bushfires

From Section 3.2 and 3.3, we know that temperature, rainfall, and fire are related, but how closely are they related? In this part, we mainly explore the correlation coefficient between them.

The correlation between rainfall, temperature and bushfires

Figure 3.11: The correlation between rainfall, temperature and bushfires

From Figure 3.11, it seems that the rainfall and bushfires have negative correlation, suggesting that the more rainfall and the less bushfires. On the contrary, the higher temperature and the more bushfires, although the correlation between these two variables is slightly small, while the relationship between them still can be evaluated. Moreover, the rainfall will be declined when the temperature would get higher. Temperatures will impact the rate of evaporation, with higher temperatures leading to faster soil moisture loss(Hausfather 2018).

In conclusion, the main climatic conditions of bushfire is hot and dry(G. J. van Oldenborgh et al. 2020). The graph of annual rainfall and temperature show that the hottest and driest year is 2019, which has the most massive bushfires in Australia as well. Therefore, as the combination of arid and severe hot conditions adds up to more powerful fires, indicating that declines in rainfall and increases in temperature have likely been a primary driver of increases in wildfire area burned.

4 Limitations of analysis

This section mainly introduces two main limitations of this analysis:
- There is no regional division in the fire data. We have indistinctly divided seven states or regions according to Australia’s longitude and latitude, which may lead to bias in the analysis results for location.
- The temperature and rainfall data include only some major cities, and comparing with the fire data, the sample is too small. Therefore, the analysis of the link between fires and climate data in Section 3 is not accurate and will cause deviation in results.

5 Conclusions

This research briefly analyzes when and where bushfires are more likely to occur and the climate conditions under which they occur. And we find that the bushfires are prone to the month from August and November every year, and the Northern Territory and Western Australia are the most prone to fires. Moreover, high temperature and drought are critical climatic conditions for the occurrence of bushfires. For future research, it will be interesting to explore how to prevent bushfires in terms of climate conditions and to analyze the effects of climate change in bushfires.

Acknowlegments

The authors would like to thank all the contributors to the following R package: Wickham et al. (2019), Wickham (2016), Wickham, Hester, and Francois (2018), Cheng, Karambelkar, and Xie (2019), Ryan and Ulrich (2020), Müller (2017), R Core Team (2020), Arnold (2019), Wickham et al. (2020), Vanderkam et al. (2018), Grolemund and Wickham (2011), Schloerke et al. (2020), Rudis (2020).

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